Logistic Regression: A Self-Learning Text

✍ Scribed by David G. Kleinbaum, Mitchel Klein (auth.)

• Publisher: Springer-Verlag New York
• Year: 2010
• Tongue: English
• Leaves: 708
• Series: Statistics for Biology and Health
• Edition: 3
• Category: Library

✦ Synopsis

This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecturer. This edition includes three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams.

Like previous editions, this textbook provides a highly readable description of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regression methods courses.

The new chapters are:

• Additional Modeling Strategy Issues, including strategy with several exposures, screening variables, collinearity, influential observations and multiple-testing

• Assessing Goodness to Fit for Logistic Regression

• Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves

The Computer Appendix provides step-by-step instructions for using STATA (version 10.0), SAS (version 9.2), and SPSS (version 16) for procedures described in the main text.

David Kleinbaum is Professor of Epidemiology at Emory University Rollins School of Public Health in Atlanta, Georgia. Dr. Kleinbaum is internationally known for his innovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has taught more than 200 courses worldwide. The recipient of numerous teaching awards, he received the first Association of Schools of Public Health Pfizer Award for Distinguished Career Teaching in 2005.

Mitchel Klein is Research Assistant Professor with a joint appointment in the Environmental and Occupational Health Department and the Epidemiology Department at Emory University Rollins School of Public Health. He has successfully designed and taught epidemiologic methods physicians at Emory’s Master of Science in Clinical Research Program. Dr. Klein is co-author with Dr. Kleinbaum of the second edition of Survival Analysis-A Self-Learning Text.

✦ Table of Contents

Front Matter....Pages i-xvii
Introduction to Logistic Regression....Pages 1-39
Important Special Cases of the Logistic Model....Pages 41-71
Computing the Odds Ratio in Logistic Regression....Pages 73-101
Maximum Likelihood Techniques: An Overview....Pages 103-127
Statistical Inferences Using Maximum Likelihood Techniques....Pages 129-164
Modeling Strategy Guidelines....Pages 165-202
Modeling Strategy for Assessing Interaction and Confounding....Pages 203-239
Additional Modeling Strategy Issues....Pages 241-299
Assessing Goodness of Fit for Logistic Regression....Pages 301-343
Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves....Pages 345-387
Analysis of Matched Data Using Logistic Regression....Pages 389-428
Polytomous Logistic Regression....Pages 429-462
Ordinal Logistic Regression....Pages 463-488
Logistic Regression for Correlated Data: GEE....Pages 489-538
GEE Examples....Pages 539-565
Other Approaches for Analysis of Correlated Data....Pages 567-598
Back Matter....Pages 599-701

✦ Subjects

Statistics for Life Sciences, Medicine, Health Sciences; Epidemiology; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law